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1 change: 1 addition & 0 deletions docs/docs.json
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Expand Up @@ -377,6 +377,7 @@
"guides/example-projects/claude-changelog-generator",
"guides/example-projects/claude-github-wiki",
"guides/example-projects/claude-thinking-chatbot",
"guides/example-projects/cursor-background-agent",
"guides/example-projects/human-in-the-loop-workflow",
"guides/example-projects/mastra-agents-with-memory",
"guides/example-projects/meme-generator-human-in-the-loop",
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105 changes: 105 additions & 0 deletions docs/guides/example-projects/cursor-background-agent.mdx
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---
title: "Background Cursor agent using the Cursor CLI"
sidebarTitle: "Cursor background agent"
description: "Run Cursor's headless CLI agent in a Trigger.dev task and stream the live output to the frontend using Trigger.dev Realtime Streams."
---

import RealtimeLearnMore from "/snippets/realtime-learn-more.mdx";

## Overview

This example runs [Cursor's headless CLI](https://cursor.com/cli) in a Trigger.dev task. The agent spawns as a child process, and its NDJSON stdout is parsed and piped to the browser in real-time using [Realtime Streams](/realtime/react-hooks/streams). The result is a live terminal UI that renders each Cursor event (system messages, assistant responses, tool calls, results) as it happens.

**Tech stack:**

- **[Next.js](https://nextjs.org/)** for the web app (App Router with server actions)
- **[Cursor CLI](https://cursor.com)** for the headless AI coding agent
- **[Trigger.dev](https://trigger.dev)** for task orchestration, real-time streaming, and deployment

## Video

<video
controls
className="w-full aspect-video"
src="https://github.com/user-attachments/assets/459aa160-6659-478e-868f-32e74f79d21a"
></video>

**Features:**

- **Build extensions**: Installs the `cursor-agent` binary into the task container image using `addLayer`, demonstrating how to ship system binaries with your tasks
- **Realtime Streams v2**: NDJSON from a child process stdout is parsed and piped directly to the browser using `streams.define()` and `.pipe()`
- **Live terminal rendering**: Each Cursor event renders as a distinct row with auto-scroll
- **Long-running tasks**: Cursor agent runs for minutes; Trigger.dev handles lifecycle, timeouts, and retries automatically
- **Machine selection**: Uses the `medium-2x` preset for resource-intensive CLI tools
- **LLM model picker**: Switch between models from the UI before triggering a run

## GitHub repo

<Card
title="View the Cursor background agent repo"
icon="GitHub"
href="https://github.com/triggerdotdev/examples/tree/main/cursor-cli-demo"
>
Click here to view the full code for this project in our examples repository on GitHub. You can
fork it and use it as a starting point for your own project.
</Card>

## How it works

### Task orchestration

The task spawns the Cursor CLI as a child process and streams its output to the frontend:

1. A Next.js server action triggers the `cursor-agent` task with the user's prompt and selected model
2. The task spawns the Cursor CLI binary using a helper that returns a typed NDJSON stream and a `waitUntilExit()` promise
3. Each line of NDJSON stdout is parsed into typed Cursor events and piped to a Realtime Stream
4. The frontend subscribes to the stream using `useRealtimeRunWithStreams` and renders each event in a terminal UI
5. The task waits for the CLI process to exit and returns the result

### Build extension for system binaries

The example includes a custom build extension that installs the `cursor-agent` binary into the container image using `addLayer`. At runtime, the binary is copied to `/tmp` and given execute permissions; this is a workaround needed when the container runtime strips execute permissions from added layers.

```ts extensions/cursor-cli.ts
export const cursorCli = defineExtension({
name: "cursor-cli",
onBuildComplete(params) {
params.addLayer({
id: "cursor-cli",
image: {
instructions: [
`COPY cursor-agent /usr/local/bin/cursor-agent`,
`RUN chmod +x /usr/local/bin/cursor-agent`,
],
},
});
},
});
```

### Streaming with Realtime Streams v2

The stream is defined with a typed schema and piped from the child process:

```ts trigger/cursor-stream.ts
export const cursorStream = streams.define("cursor", cursorEventSchema);
```

```ts trigger/cursor-agent.ts
const { stream, waitUntilExit } = spawnCursorAgent({ prompt, model });
cursorStream.pipe(stream);
await waitUntilExit();
```

On the frontend, the `useRealtimeRunWithStreams` hook subscribes to these events and renders them as they arrive.

## Relevant code

- **Build extension + spawn helper**: [extensions/cursor-cli.ts](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/extensions/cursor-cli.ts): installs the binary and provides a typed NDJSON stream with `waitUntilExit()`
- **Task definition**: [trigger/cursor-agent.ts](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/trigger/cursor-agent.ts): spawns the CLI, pipes the stream, waits for exit
- **Stream definition**: [trigger/cursor-stream.ts](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/trigger/cursor-stream.ts): Realtime Streams v2 stream with typed schema
- **Terminal UI**: [components/terminal.tsx](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/components/terminal.tsx): renders live events using `useRealtimeRunWithStreams`
- **Event types**: [lib/cursor-events.ts](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/lib/cursor-events.ts): TypeScript types and parsers for Cursor NDJSON events
- **Trigger config**: [trigger.config.ts](https://github.com/triggerdotdev/examples/blob/main/cursor-cli-demo/trigger.config.ts): project config with the cursor CLI build extension

<RealtimeLearnMore />
1 change: 1 addition & 0 deletions docs/guides/introduction.mdx
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Expand Up @@ -56,6 +56,7 @@ Example projects are full projects with example repos you can fork and use. Thes
| [Claude changelog generator](/guides/example-projects/claude-changelog-generator) | Automatically generate professional changelogs from git commits using Claude. | — | [View the repo](https://github.com/triggerdotdev/examples/tree/main/changelog-generator) |
| [Claude GitHub wiki agent](/guides/example-projects/claude-github-wiki) | Generate and maintain GitHub wiki documentation with Claude-powered analysis. | — | [View the repo](https://github.com/triggerdotdev/examples/tree/main/claude-agent-github-wiki) |
| [Claude thinking chatbot](/guides/example-projects/claude-thinking-chatbot) | Use Vercel's AI SDK and Anthropic's Claude 3.7 model to create a thinking chatbot. | Next.js | [View the repo](https://github.com/triggerdotdev/examples/tree/main/claude-thinking-chatbot) |
| [Cursor background agent](/guides/example-projects/cursor-background-agent) | Run Cursor's headless CLI agent as a background task, streaming live output to the browser. | Next.js | [View the repo](https://github.com/triggerdotdev/examples/tree/main/cursor-cli-demo) |
| [Human-in-the-loop workflow](/guides/example-projects/human-in-the-loop-workflow) | Create audio summaries of newspaper articles using a human-in-the-loop workflow built with ReactFlow and Trigger.dev waitpoint tokens. | Next.js | [View the repo](https://github.com/triggerdotdev/examples/tree/main/article-summary-workflow) |
| [Mastra agents with memory](/guides/example-projects/mastra-agents-with-memory) | Use Mastra to create a weather agent that can collect live weather data and generate clothing recommendations. | — | [View the repo](https://github.com/triggerdotdev/examples/tree/main/mastra-agents) |
| [OpenAI Agents SDK for Python guardrails](/guides/example-projects/openai-agent-sdk-guardrails) | Use the OpenAI Agents SDK for Python to create a guardrails system for your AI agents. | — | [View the repo](https://github.com/triggerdotdev/examples/tree/main/openai-agent-sdk-guardrails-examples) |
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